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I will build automated etl pipelines and data integration in python
Python Developer , Data Engineering
I am a detail-oriented Data Engineering student with solid experience in designing end-to-end data pipelines, dimensional modeling, and database management. I am proficient in Python, SQL, and MongoDB...
About this Gig
Are you looking for a reliable, production-ready ETL pipeline to integrate, clean, and automate your data workflows? Look no further!
I specialize in building custom, high-performance data engineering pipelines using Python, SQL, and modern tools. Whether you need a simple script or a complex multi-source pipeline, I will deliver clean, maintainable, and well-tested code.
What I offer:
Multi-Source Ingestion: Extract data from REST APIs, SQL (PostgreSQL, MySQL), NoSQL (MongoDB), CSV, JSON, or Web Scraping.
Data Transformation & Validation: Clean raw data, enforce data quality gates, isolate malformed records, and apply custom business logic.
Smart Incremental Loading: Implement idempotent and watermark-based loads into your target databases.
Workflow Orchestration: Schedule and monitor pipeline runs automatically using Apache Airflow DAGs
Containerization: Package your pipeline with Docker & Docker Compose for hassle-free execution anywhere.
Robust Error Handling: Built-in retries, fallbacks, and detailed pipeline logging.
Why work with me?
Modular, clean, and optimized Python code (OOP-driven).
Deep focus on data accuracy and fault tolerance.
Clear communication and fast delivery
Destination Platform:
PostgreSQL
•
MySQL
•
Other
Tools & Platforms:
Other
My Portfolio
Other Data Engineering Services I Offer
FAQ
What do I need to provide before placing an order?
You need to provide sample data, API access/credentials (if applicable), and a brief explanation of your required output or target database.
Can you schedule the pipeline to run automatically?
Yes, I can set up automated scheduling using Apache Airflow DAGs or Dockerized task schedulers.
What happens if the source data contains missing or corrupt records?
I build custom data quality gates that quarantine malformed records without halting the entire pipeline execution.
